In both personal endeavours and professional initiatives, we often encounter a puzzling mismatch between our expectations and reality when it comes to completing tasks on time and within budget. This phenomenon is known in psychology as the planning fallacy—the tendency to underestimate the time, costs and risks associated with future tasks, despite knowing that similar tasks in the past took longer and cost more.
In this guide, we’ll dive deep into the planning fallacy: its origins, why it happens, how it affects projects of all sizes, and practical strategies you can apply to help avoid it. Whether you’re planning a home renovation, a new product launch, or simply managing your weekly tasks, these insights will help you plan more realistically and deliver more reliably.
What is the Planning Fallacy?
The term “planning fallacy” was introduced by psychologists Daniel Kahneman and Amos Tversky in 1979. They defined it as the “tendency to underestimate the amount of time needed to complete a future task, due in part to the reliance on overly optimistic performance scenarios.”
In essence, it means we predict that a task will be finished sooner than it actually will. We are overly confident in our ability to deliver—and we discount or ignore evidence to the contrary.
Some of the key characteristics of the planning fallacy include:
It affects not only individuals but also teams and organisations: predictions about one’s own tasks are generally more optimistic than reality.
The errors in estimation arise from biases and wishful thinking—rather than purely random miscalculations.
Interestingly, even when people have experienced past failures, they still fall foul of the planning fallacy.
The effect occurs across personality types, cultures, task sizes and time horizons—so nearly everyone is vulnerable.
Put simply: you might plan that a website redesign will take two weeks, but it ends up taking four. You budget for a small repair job that cost $2,000, and the final bill is $6,000. The planning fallacy shows up everywhere—and to beat it, you first need to understand why it happens.
Why Do We Fall for the Planning Fallacy?
Several cognitive and motivational biases contribute to the planning fallacy. Here are the main culprits:
1. Optimism bias and wishful thinking
We tend to see our glass half-full rather than half-empty. When planning, we focus on the best‐case scenario: “Everything will go smoothly,” “We’ll have the right resources,” “No unexpected setbacks.” Because we like positive stories, we expect ourselves to succeed and discount the possibility of failure.
For example, a repair contractor might say, “That’ll take five minutes,” despite many five-minute tasks stretching out into hours.
2. Resistance to updating plans in light of new information
When new information arrives that indicates a delay or risk, many planners dismiss or minimise it rather than recalibrating. Anchoring bias can cause them to cling to the original (optimistic) estimate instead of adjusting.
Because admitting that you’re off-track can feel like admitting you were wrong, it’s easier—though less wise—to ignore it.
3. Avoidance of negative information
Nobody likes being the “cynic” who says “it won’t work.” Thus, teams often suppress bad news (or distort it) to preserve a positive outlook. That means early warning signs of delay or cost overrun get ignored or under-played.
In effect, the team’s desire to be seen as capable, efficient, and optimistic blinds them to obstacles.
4. Motivated reasoning
Our reasoning often supports our desired outcomes. If the client wants the project done in two weeks, we may convince ourselves we can do it—even if the truth is different. Our brain filters evidence that supports our belief and ignores evidence that doesn’t.
Together, these biases combine to make unreality feel plausible, leading us to build plans that are too optimistic, too narrow, and lacking contingency.
The Real-World Effects of the Planning Fallacy
Falling for the planning fallacy isn’t just a mild annoyance—it has serious consequences. Whether you’re overseeing small tasks or major infrastructure projects, the effects can ripple out in damaging ways.
Misjudged timelines
Projects often extend far beyond the original timeline because the planner did not allow for experimentation, failure, rework or unforeseen issues. This is particularly pronounced in innovative or complex tasks which inherently have more uncertainty.
For example, an initiative that looked simple at the outset morphs into a complex beast, and the original two-month timeline becomes six.
Under-budgeting resources
When you think something will take less time, you also think it will cost less. You may assign fewer people than needed and allocate inadequate budget or fewer supports. The result: resource strain, burnout, quality drop or failure.
Ignoring external risks
When you focus on the best-case scenario, you overlook external factors: regulation, market shifts, technical debt, vendor readiness, dependency on other teams. Because you ignored that possibility, you’re blindsided when they occur.
Increased pressure and burnout
Teams feel the squeeze when they commit to unrealistic deadlines. Deliverables become rushed, corners get cut, stress rises, morale drops. Over time this can damage both people and outcomes.
Stifled innovation
Projects that aim to break new ground are particularly vulnerable. Because they carry uncertainty, plans often fail to allow for iteration or learning. When you underestimate time and cost, you’re forced to cut corners—undermining the innovative goal.
Historical examples are instructive
The construction of the Sydney Opera House is one of the most cited examples. Initially budgeted at US $7 million with a completion time of six years, it opened 16 years later at a cost of approximately US $102 million.
The Canadian Pacific Railway was supposed to be completed by 1881 for C$25 million, but actually finished four years later and borrowed an additional C$22.5 million.
The launch of the Healthcare.gov website in the U.S. is another example: projected cost roughly US $292 million but actual spend topped US $2.1 billion.
These are extreme, but similar patterns—under-estimated time, cost overruns, unplanned risk—occur in everyday tasks and small organisations too.
Strategies to Avoid the Planning Fallacy
Recognising that you are susceptible to the planning fallacy is the first step. The next step is actively building processes and habits to counter it. Here are evidence-based techniques to make your planning more realistic and robust.
1. Trust historical data (reference-class forecasting)
Instead of relying solely on what you think will happen, look at what has happened in similar past tasks or projects. Identify a “reference class” (a set of comparable tasks), gather data on how long they took, what risks emerged and the final results.
Steps to apply this:
Identify comparable previous projects (within your organisation or externally)
Document the actual time, cost, resource usage, obstacles and deviations
Use this as baseline for setting new estimates, not just intuition
Build contingency buffers based on empirical deviations
Historical data forces you to ground your optimism in reality—and helps reveal hidden risks you might otherwise ignore.
2. Set “if-then” implementation intentions
Break down tasks and frame them with conditional statements: “If X happens, then I will do Y.” These are behavioral prompts that make you ready for potential obstacles or variations.
Examples:
If a key team member is delayed, then I’ll reassign half his workload to backup resource A.
If client feedback is late, then I’ll adjust the milestone by two days and alert stakeholders.
If the research phase uncovers unexpected complexity, then I’ll add a buffer of one week to the schedule.
By explicitly planning responses to likely issues, you reduce the risk of being derailed by “surprises”.
3. Use the segmentation effect (break the project into smaller parts)
Large tasks attract vague and optimistic estimates. Instead, divide your project into smaller, clearly defined segments or tasks. For each segment, estimate time and resources, taking into account research, discussion, experimentation, revision and coordination. ClickUp
Benefits:
Smaller units are easier to estimate accurately
You can apply historical data to each segment rather than one monolithic estimate
You’re more likely to detect early deviations and adjust sooner
It encourages thinking about “non-work work” (meetings, handoffs, downtime) which often gets overlooked
4. Apply three-point estimation
Rather than a single estimate, use three scenarios for each task:
Optimistic: everything goes well, minimal issues
Most likely: realistic scenario based on experience and data
Pessimistic: considerable delays/issues and worst-case outcomes
Then compute a weighted average (or simply use the most likely plus a buffer). This method forces you to confront both best and worst cases, reducing bias.
For example:
Optimistic: 4 days
Most likely: 6 days
Pessimistic: 10 days
Weighted average might place the estimate around 7 or 8 days rather than the naïve 4 or 6.
5. Don’t reinvent the wheel—leverage templates and prior work
When teams always start from scratch, they are tapping into intuition rather than structured evidence. Use templates, processes, checklists and frameworks derived from past projects. This helps anchor planning in what’s already been done, reducing the chance of over-optimistic novelty.
For instance:
Project kickoff document that includes known dependencies, risks and assumptions
Time‐tracking logs or resource-history spreadsheets from previous work
Risk register templates populated with common issues that recur
Using what has worked (and what didn’t) helps ground your planning in lived experience rather than guesswork.
6. Be a thoughtful pessimist (or realistic optimist)
This may sound counterintuitive—but adopting a mildly pessimistic mindset can be helpful. Ask “What could go wrong?” and build buffers and contingencies accordingly. Reserve some capacity, allocate extra time, plan for interruptions.
More realistic thinking leads to better risk mitigation. Project managers who consider worst-case scenarios tend to deliver closer to on-time and on-budget.
7. Continually monitor and revise
Even with the best planning, things change. Make your plan living, not locked. Include regular check-ins, data updates, milestone reviews, and allow for re-estimation. If earlier segments show overruns, adjust the rest of the plan accordingly rather than hoping to catch up magically.
8. Build a culture of realistic estimation
Encourage transparency and honest reporting. Reward teams not only for “on-time” deliverables but also for accurate estimations and identifying risks early. Shift away from “we must hit this deadline no matter what” to “we will deliver by this date unless new information arises, and we will flag it early if it does.”
Applying It to Everyday and Professional Life
While these strategies may sound technical, they’re highly applicable across many scenarios—from personal tasks to large organisational projects.
Personal tasks
Want to declutter your house? Instead of estimating “2 hours to clean the garage”, look back at similar efforts: maybe it took you 4 hours last time. So set a more realistic target.
Planning a presentation? Break it down: research, outline, draft slides, practice. Estimate each part with three-point estimates.
Launching a side-hustle? Treat it as a project: list tasks, estimate with reference data (how long did prior gigs take?), plan for delays (side-hustles get squeezed by day job).
Professional and organisational projects
Software development: Use historical sprint data to estimate upcoming sprints. Break features into user stories, apply three-point estimation, give time for bug fixes & rework.
Marketing campaigns: Instead of “We’ll go live in four weeks,” look at prior campaigns: creative approvals, asset creation, stakeholder feedback—all take time. Build in buffer accordingly.
Construction and engineering: Complex, high-uncertainty projects are especially vulnerable. Reference class forecasting is essential—look at terrain, weather, supply chain, regulatory approvals.
Strategic initiatives: Innovation projects often require iteration, prototyping, so plan for “fail fast and iterate.” If you assume you’ll nail it first time, you’re setting yourself up for delay.
Common Pitfalls and How to Spot Them
Despite knowing the strategies, teams frequently fall into the same traps. Here are warning signs that the planning fallacy is at play—and how to recognise them:
Single‐point estimate without buffer: If your estimate is “3 weeks” and there’s no alternative scenario or contingency, this is a red flag.
“We can do it because we’re fast” thinking: Overconfidence based on past success can lead to ignoring actual complexity.
Ignoring past performance data: If no one looks at what similar tasks have taken historically, the estimate is built purely on wishful thinking.
Treating the plan as immutable: If there’s no mechanism for revising the plan in light of new data (e.g., delays, extra work, dependencies), the project becomes rigid and brittle.
Downplaying potential problems: If the team avoids discussing “what could go wrong,” you’re likely underestimating risk.
Saying “We’ll just add more people later”: Increasing resources often has diminishing returns and coordination overhead—so planning for bigger team size as a fix may not actually reduce time.
By being vigilant for these signs, you can introduce corrective steps early rather than waiting until the project is off-track.
Putting It All Together: A Step-By-Step Framework
Here’s a practical framework you can follow whenever you plan a project or task. Use this to embed more realistic estimation habits:
Define the scope clearly
What exactly needs to be done?
What are the deliverables, the dependencies, potential uncertainties?
Break the work into smaller components (segmentation)
List sub-tasks, phases, dependencies, research, iteration cycles.
Gather historical reference data
Look at similar past work: how long did each sub-task take? What were the deviations?
Document the outcomes: actual vs estimated, resource usage, risks encountered.
Estimate each component using three-point estimation
For each sub-task: optimistic scenario, most likely scenario, pessimistic scenario.
Compute weighted or reasoned average.
Add a contingency buffer (e.g., + 20-30%) based on the difference between actual and estimated in past tasks.
Plan for risk explicitly
Ask: What could go wrong? What dependencies exist? What external factors could impact this?
Formulate “if-then” implementation intentions: if this happens, then we will do that.
Create the schedule and budget including buffers
Sum the component estimates, include contingency.
Make sure stakeholders understand that this is a realistic plan with built-in buffer—not an aspirational deadline.
Secure realistic commitments
Communicate openly with stakeholders about the plan and its assumptions.
Avoid over-promising. Set expectations about risk and potential variation.
Monitor progress and revise
At each milestone, compare actual vs planned.
If tasks are overrunning, re-estimate remaining tasks rather than assume you will catch up.
Flag issues early and adjust schedule, resources, or scope if required.
Capture learning and update reference data
After completion, document the actual time taken, cost, deviations, risks experienced.
Feed that back into your historical data pool so the next project benefits from better information.
By following this framework consistently, you embed a culture of realistic planning, continual learning, and risk awareness.
Why It’s Worth Investing in Realistic Planning
You might ask: “Why go through all this effort? Isn’t a simple estimate good enough?” The answer is: yes, you can just guess—but what you’ll pay for it is often higher risk, repeated delays, frustrated stakeholders and stressed teams.
Here are the pay-offs for better planning:
More reliable delivery: When timelines and budgets are realistic, you’re far more likely to deliver on them, maintain stakeholder trust and reduce surprise over‐runs.
Reduced stress and higher morale: Teams know what to expect, aren’t constantly chasing unrealistic goals and can manage work in a sustainable way.
Better resource management: You’re less likely to over‐allocate or under-allocate, and you’ll have contingency built in rather than scrambling at the last minute.
Improved innovation and iteration: When projects build in realistic time for experimentation and learning, outcomes are better rather than rushed.
Stronger decision-making: With grounded estimates and risk-aware plans, you make decisions based on data and reality—not wishful thinking.
In short: realistic planning isn’t about pessimism—it’s about effective realism. You acknowledge the unknowns, allow for variation, build in safeguards, and deliver with confidence.
The Planning Fallacy Will Persist—But You Can Out-Plan It
Even with awareness and the best methods, the planning fallacy will continue to exist. Human nature biases us toward optimism, novelty and underestimation of risk. That doesn’t mean we’re doomed to fail—far from it. It simply means we must actively guard against it.
By understanding the fallacy, recognising when it’s at work, and applying structured methods—such as historical data, segmentation, three-point estimation, contingency planning and continual monitoring—you increase your odds of success dramatically.
Whether you are organizing your next home renovation, launching a new product, or delivering a strategic initiative at work, the same principles apply: plan realistically, account for uncertainty, build in buffers, learn from past experience, and adjust when things change.
As the psychologist Daniel Kahneman noted, “Most of us view the world as more benign than it really is, our attributes as more favorable than they truly are, and the goals we adopt as more achievable than they are likely to be.” By keeping this in mind, and building systems to counteract it, you’ll find yourself delivering more consistently, with less stress and more satisfaction.
Expect surprises, plan for them, and you’ll be better prepared when they arrive.
Read More: How to Use the Interleaving Study Method for Better Learning
